Pandas Profiling Report

Dataset statistics

Number of variables	18
Number of observations	1000
Missing cells	638
Missing cells (%)	3.5%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	140.8 KiB
Average record size in memory	144.1 B

Variable types

CAT	11
NUM	7

Reproduction

Analysis started	2020-07-18 05:01:03.680504
Analysis finished	2020-07-18 05:02:18.093883
Duration	1 minute and 14.41 seconds
Version	pandas-profiling v2.8.0
Command line	`pandas_profiling --config_file config.yaml [YOUR_FILE.csv]`
Download configuration	config.yaml

Warnings

`Title` has a high cardinality: 999 distinct values	High cardinality
`Director` has a high cardinality: 644 distinct values	High cardinality
`Actors` has a high cardinality: 996 distinct values	High cardinality
`Actor-1` has a high cardinality: 525 distinct values	High cardinality
`Actor-2` has a high cardinality: 692 distinct values	High cardinality
`Actor-3` has a high cardinality: 788 distinct values	High cardinality
`Actor-4` has a high cardinality: 897 distinct values	High cardinality
`Revenue (Millions)` has 128 (12.8%) missing values	Missing
`Metascore` has 64 (6.4%) missing values	Missing
`Genre-2` has 105 (10.5%) missing values	Missing
`Genre-3` has 340 (34.0%) missing values	Missing
`Title` is uniformly distributed	Uniform
`Director` is uniformly distributed	Uniform
`Actors` is uniformly distributed	Uniform
`Actor-2` is uniformly distributed	Uniform
`Actor-3` is uniformly distributed	Uniform
`Actor-4` is uniformly distributed	Uniform
`Rank` has unique values	Unique
`Description` has unique values	Unique

Rank
Real number (ℝ_≥0)

UNIQUE

Distinct count	1000
Unique (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	500.5
Minimum	1
Maximum	1000
Zeros	0
Zeros (%)	0.0%
Memory size	7.8 KiB

Quantile statistics

Minimum	1
5-th percentile	50.95
Q1	250.75
median	500.5
Q3	750.25
95-th percentile	950.05
Maximum	1000
Range	999
Interquartile range (IQR)	499.5

Descriptive statistics

Standard deviation	288.8194361
Coefficient of variation (CV)	0.5770618104
Kurtosis	-1.2
Mean	500.5
Median Absolute Deviation (MAD)	250
Skewness	0
Sum	500500
Variance	83416.66667

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1000	1	0.1%
329	1	0.1%
342	1	0.1%
341	1	0.1%
340	1	0.1%
339	1	0.1%
338	1	0.1%
337	1	0.1%
336	1	0.1%
335	1	0.1%
Other values (990)	990	99.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	0.1%
2	1	0.1%
3	1	0.1%
4	1	0.1%
5	1	0.1%

Value	Count	Frequency (%)
1000	1	0.1%
999	1	0.1%
998	1	0.1%
997	1	0.1%
996	1	0.1%

Title
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count	999
Unique (%)	99.9%
Missing	0
Missing (%)	0.0%
Memory size	7.8 KiB

The Host	2
Easy A	1
The Maze Runner	1
Neighbors 2: Sorority Rising	1
Alexander and the Terrible, Horrible, No Good, Very Bad Day	1
Other values (994)	994

Common Values
Length

Value	Count	Frequency (%)
The Host	2	0.2%
Easy A	1	0.1%
The Maze Runner	1	0.1%
Neighbors 2: Sorority Rising	1	0.1%
Alexander and the Terrible, Horrible, No Good, Very Bad Day	1	0.1%
Project X	1	0.1%
The Thinning	1	0.1%
Pain & Gain	1	0.1%
Dark Places	1	0.1%
Scott Pilgrim vs. the World	1	0.1%
Other values (989)	989	98.9%

Length

Max length	61
Median length	13
Mean length	14.539
Min length	2

Description
Categorical

UNIQUE

Distinct count	1000
Unique (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	7.8 KiB

A New York writer on sex and love is finally getting married to her Mr. Big. But her three best girlfriends must console her after one of them inadvertently leads Mr. Big to jilt her.	1
A dying CIA agent trying to reconnect with his estranged daughter is offered an experimental drug that could save his life in exchange for one last assignment.	1
When their new next-door neighbors turn out to be a sorority even more debaucherous than the fraternity previously living there, Mac and Kelly team with their former enemy, Teddy, to bring the girls down.	1
Disgruntled Korean War veteran Walt Kowalski sets out to reform his neighbor, a Hmong teenager who tried to steal Kowalski's prized possession: a 1972 Gran Torino.	1
Three years after Mike bowed out of the stripper life at the top of his game, he and the remaining Kings of Tampa hit the road to Myrtle Beach to put on one last blow-out performance.	1
Other values (995)	995

Common Values
Length

Value	Count	Frequency (%)
A New York writer on sex and love is finally getting married to her Mr. Big. But her three best girlfriends must console her after one of them inadvertently leads Mr. Big to jilt her.	1	0.1%
A dying CIA agent trying to reconnect with his estranged daughter is offered an experimental drug that could save his life in exchange for one last assignment.	1	0.1%
When their new next-door neighbors turn out to be a sorority even more debaucherous than the fraternity previously living there, Mac and Kelly team with their former enemy, Teddy, to bring the girls down.	1	0.1%
Disgruntled Korean War veteran Walt Kowalski sets out to reform his neighbor, a Hmong teenager who tried to steal Kowalski's prized possession: a 1972 Gran Torino.	1	0.1%
Three years after Mike bowed out of the stripper life at the top of his game, he and the remaining Kings of Tampa hit the road to Myrtle Beach to put on one last blow-out performance.	1	0.1%
In the aftermath of a family tragedy, an aspiring author is torn between love for her childhood friend and the temptation of a mysterious outsider. Trying to escape the ghosts of her past, she is swept away to a house that breathes, bleeds - and remembers.	1	0.1%
For three Border Patrol agents working a remote desert checkpoint, the contents of one car will reveal an insidious plot within their own ranks. The next 24 hours will take them on a treacherous journey that could cost them their lives.	1	0.1%
Two sisters decide to throw one last house party before their parents sell their family home.	1	0.1%
Manolo, a young man who is torn between fulfilling the expectations of his family and following his heart, embarks on an adventure that spans three fantastic worlds where he must face his greatest fears.	1	0.1%
An elite military unit comprised of special operatives known as G.I. Joe, operating out of The Pit, takes on an evil organization led by a notorious arms dealer.	1	0.1%
Other values (990)	990	99.0%

Length

Max length	421
Median length	159
Mean length	163.232
Min length	42

Director
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count	644
Unique (%)	64.4%
Missing	0
Missing (%)	0.0%
Memory size	7.8 KiB

Ridley Scott	8
M. Night Shyamalan	6
Paul W.S. Anderson	6
David Yates	6
Michael Bay	6
Other values (639)	968

Common Values
Length

Value	Count	Frequency (%)
Ridley Scott	8	0.8%
M. Night Shyamalan	6	0.6%
Paul W.S. Anderson	6	0.6%
David Yates	6	0.6%
Michael Bay	6	0.6%
Christopher Nolan	5	0.5%
Denis Villeneuve	5	0.5%
Martin Scorsese	5	0.5%
Antoine Fuqua	5	0.5%
Woody Allen	5	0.5%
Other values (634)	943	94.3%

Length

Max length	32
Median length	13
Mean length	13.139
Min length	3

Actors
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count	996
Unique (%)	99.6%
Missing	0
Missing (%)	0.0%
Memory size	7.8 KiB

Daniel Radcliffe, Emma Watson, Rupert Grint, Michael Gambon	2
Gerard Butler, Aaron Eckhart, Morgan Freeman,Angela Bassett	2
Shia LaBeouf, Megan Fox, Josh Duhamel, Tyrese Gibson	2
Jennifer Lawrence, Josh Hutcherson, Liam Hemsworth, Woody Harrelson	2
Samuel L. Jackson, Julianna Margulies, Nathan Phillips, Rachel Blanchard	1
Other values (991)	991

Common Values
Length

Value	Count	Frequency (%)
Daniel Radcliffe, Emma Watson, Rupert Grint, Michael Gambon	2	0.2%
Gerard Butler, Aaron Eckhart, Morgan Freeman,Angela Bassett	2	0.2%
Shia LaBeouf, Megan Fox, Josh Duhamel, Tyrese Gibson	2	0.2%
Jennifer Lawrence, Josh Hutcherson, Liam Hemsworth, Woody Harrelson	2	0.2%
Samuel L. Jackson, Julianna Margulies, Nathan Phillips, Rachel Blanchard	1	0.1%
Kurt Russell, Zoë Bell, Rosario Dawson, Vanessa Ferlito	1	0.1%
Owen Wilson, Rachel McAdams, Kathy Bates, Kurt Fuller	1	0.1%
Casey Affleck, Chiwetel Ejiofor, Anthony Mackie,Aaron Paul	1	0.1%
Emma Roberts, Dave Franco, Emily Meade, Miles Heizer	1	0.1%
Kristen Stewart, Robert Pattinson, Billy Burke,Sarah Clarke	1	0.1%
Other values (986)	986	98.6%

Length

Max length	77
Median length	58
Mean length	58.288
Min length	43

Year
Real number (ℝ_≥0)

Distinct count	11
Unique (%)	1.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2012.783
Minimum	2006
Maximum	2016
Zeros	0
Zeros (%)	0.0%
Memory size	7.8 KiB

Quantile statistics

Minimum	2006
5-th percentile	2007
Q1	2010
median	2014
Q3	2016
95-th percentile	2016
Maximum	2016
Range	10
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	3.205961508
Coefficient of variation (CV)	0.00159280037
Kurtosis	-0.8219639755
Mean	2012.783
Median Absolute Deviation (MAD)	2
Skewness	-0.6898787091
Sum	2012783
Variance	10.27818919

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
2016	297	29.7%
2015	127	12.7%
2014	98	9.8%
2013	91	9.1%
2012	64	6.4%
2011	63	6.3%
2010	60	6.0%
2007	53	5.3%
2008	52	5.2%
2009	51	5.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2006	44	4.4%
2007	53	5.3%
2008	52	5.2%
2009	51	5.1%
2010	60	6.0%

Value	Count	Frequency (%)
2016	297	29.7%
2015	127	12.7%
2014	98	9.8%
2013	91	9.1%
2012	64	6.4%

Runtime (Minutes)
Real number (ℝ_≥0)

Distinct count	94
Unique (%)	9.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	113.172
Minimum	66
Maximum	191
Zeros	0
Zeros (%)	0.0%
Memory size	7.8 KiB

Quantile statistics

Minimum	66
5-th percentile	88
Q1	100
median	111
Q3	123
95-th percentile	150
Maximum	191
Range	125
Interquartile range (IQR)	23

Descriptive statistics

Standard deviation	18.81090817
Coefficient of variation (CV)	0.1662152138
Kurtosis	0.8583211032
Mean	113.172
Median Absolute Deviation (MAD)	12
Skewness	0.8467127314
Sum	113172
Variance	353.8502663

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
108	31	3.1%
100	28	2.8%
117	27	2.7%
110	26	2.6%
106	26	2.6%
118	26	2.6%
102	25	2.5%
112	24	2.4%
104	23	2.3%
123	23	2.3%
Other values (84)	741	74.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
66	1	0.1%
73	2	0.2%
80	2	0.2%
81	5	0.5%
82	1	0.1%

Value	Count	Frequency (%)
191	1	0.1%
187	1	0.1%
180	3	0.3%
172	1	0.1%
170	1	0.1%

Rating
Real number (ℝ_≥0)

Distinct count	55
Unique (%)	5.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	6.723199999999999
Minimum	1.9
Maximum	9.0
Zeros	0
Zeros (%)	0.0%
Memory size	7.8 KiB

Quantile statistics

Minimum	1.9
5-th percentile	5.1
Q1	6.2
median	6.8
Q3	7.4
95-th percentile	8.1
Maximum	9
Range	7.1
Interquartile range (IQR)	1.2

Descriptive statistics

Standard deviation	0.9454287893
Coefficient of variation (CV)	0.1406218451
Kurtosis	1.322270288
Mean	6.7232
Median Absolute Deviation (MAD)	0.6
Skewness	-0.7431419408
Sum	6723.2
Variance	0.8938355956

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
7.1	52	5.2%
6.7	48	4.8%
7	46	4.6%
6.3	44	4.4%
6.6	42	4.2%
7.2	42	4.2%
7.3	42	4.2%
6.5	40	4.0%
7.8	40	4.0%
6.2	37	3.7%
Other values (45)	567	56.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1.9	1	0.1%
2.7	2	0.2%
3.2	1	0.1%
3.5	2	0.2%
3.7	2	0.2%

Value	Count	Frequency (%)
9	1	0.1%
8.8	2	0.2%
8.6	3	0.3%
8.5	6	0.6%
8.4	4	0.4%

Votes
Real number (ℝ_≥0)

Distinct count	997
Unique (%)	99.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	169808.255
Minimum	61
Maximum	1791916
Zeros	0
Zeros (%)	0.0%
Memory size	7.8 KiB

Quantile statistics

Minimum	61
5-th percentile	1260.35
Q1	36309
median	110799
Q3	239909.75
95-th percentile	526551.85
Maximum	1791916
Range	1791855
Interquartile range (IQR)	203600.75

Descriptive statistics

Standard deviation	188762.6475
Coefficient of variation (CV)	1.111622327
Kurtosis	11.3126809
Mean	169808.255
Median Absolute Deviation (MAD)	88402
Skewness	2.507918483
Sum	169808255
Variance	3.56313371e+10

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1427	2	0.2%
97141	2	0.2%
291	2	0.2%
531112	1	0.1%
702	1	0.1%
47804	1	0.1%
226619	1	0.1%
76469	1	0.1%
125693	1	0.1%
174553	1	0.1%
Other values (987)	987	98.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
61	1	0.1%
96	1	0.1%
102	1	0.1%
115	1	0.1%
164	1	0.1%

Value	Count	Frequency (%)
1791916	1	0.1%
1583625	1	0.1%
1222645	1	0.1%
1047747	1	0.1%
1045588	1	0.1%

Revenue (Millions)
Real number (ℝ_≥0)

MISSING

Distinct count	814
Unique (%)	93.3%
Missing	128
Missing (%)	12.8%
Infinite	0
Infinite (%)	0.0%

Mean	82.95637614678898
Minimum	0.0
Maximum	936.63
Zeros	1
Zeros (%)	0.1%
Memory size	7.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0.211
Q1	13.27
median	47.985
Q3	113.715
95-th percentile	293.88
Maximum	936.63
Range	936.63
Interquartile range (IQR)	100.445

Descriptive statistics

Standard deviation	103.2535405
Coefficient of variation (CV)	1.244672746
Kurtosis	10.60763453
Mean	82.95637615
Median Absolute Deviation (MAD)	41.285
Skewness	2.592515866
Sum	72337.96
Variance	10661.29362

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0.03	7	0.7%
0.01	5	0.5%
0.04	4	0.4%
0.02	4	0.4%
0.32	4	0.4%
0.05	4	0.4%
1.29	3	0.3%
0.15	3	0.3%
2.2	3	0.3%
0.54	3	0.3%
Other values (804)	832	83.2%
(Missing)	128	12.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
0.01	5	0.5%
0.02	4	0.4%
0.03	7	0.7%
0.04	4	0.4%

Value	Count	Frequency (%)
936.63	1	0.1%
760.51	1	0.1%
652.18	1	0.1%
623.28	1	0.1%
533.32	1	0.1%

Metascore
Real number (ℝ_≥0)

MISSING

Distinct count	84
Unique (%)	9.0%
Missing	64
Missing (%)	6.4%
Infinite	0
Infinite (%)	0.0%

Mean	58.98504273504273
Minimum	11.0
Maximum	100.0
Zeros	0
Zeros (%)	0.0%
Memory size	7.8 KiB

Quantile statistics

Minimum	11
5-th percentile	31
Q1	47
median	59.5
Q3	72
95-th percentile	85
Maximum	100
Range	89
Interquartile range (IQR)	25

Descriptive statistics

Standard deviation	17.19475702
Coefficient of variation (CV)	0.2915104614
Kurtosis	-0.6122051468
Mean	58.98504274
Median Absolute Deviation (MAD)	12.5
Skewness	-0.1238873467
Sum	55210
Variance	295.6596691

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
66	25	2.5%
72	25	2.5%
68	25	2.5%
64	24	2.4%
57	23	2.3%
51	22	2.2%
65	22	2.2%
48	21	2.1%
81	21	2.1%
76	21	2.1%
Other values (74)	707	70.7%
(Missing)	64	6.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
11	1	0.1%
15	1	0.1%
16	1	0.1%
18	4	0.4%
19	1	0.1%

Value	Count	Frequency (%)
100	1	0.1%
99	1	0.1%
98	1	0.1%
96	4	0.4%
95	3	0.3%

Actor-1
Categorical

HIGH CARDINALITY

Distinct count	525
Unique (%)	52.5%
Missing	0
Missing (%)	0.0%
Memory size	7.8 KiB

Mark Wahlberg	11
Christian Bale	11
Jake Gyllenhaal	9
Denzel Washington	9
Leonardo DiCaprio	9
Other values (520)	951

Common Values
Length

Value	Count	Frequency (%)
Mark Wahlberg	11	1.1%
Christian Bale	11	1.1%
Jake Gyllenhaal	9	0.9%
Denzel Washington	9	0.9%
Leonardo DiCaprio	9	0.9%
Brad Pitt	9	0.9%
Adam Sandler	9	0.9%
Will Smith	9	0.9%
Tom Hanks	8	0.8%
Daniel Radcliffe	8	0.8%
Other values (515)	908	90.8%

Length

Max length	23
Median length	13
Mean length	13.132
Min length	7

Actor-2
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count	692
Unique (%)	69.2%
Missing	0
Missing (%)	0.0%
Memory size	7.8 KiB

Cate Blanchett	8
Michelle Monaghan	6
Rose Byrne	6
Jonah Hill	5
Robert Pattinson	5
Other values (687)	970

Common Values
Length

Value	Count	Frequency (%)
Cate Blanchett	8	0.8%
Michelle Monaghan	6	0.6%
Rose Byrne	6	0.6%
Jonah Hill	5	0.5%
Robert Pattinson	5	0.5%
Kristen Wiig	5	0.5%
Emma Watson	5	0.5%
Hugh Jackman	5	0.5%
Anne Hathaway	5	0.5%
Aaron Eckhart	4	0.4%
Other values (682)	946	94.6%

Length

Max length	27
Median length	14
Mean length	14.125
Min length	6

Actor-3
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count	788
Unique (%)	78.8%
Missing	0
Missing (%)	0.0%
Memory size	7.8 KiB

Morgan Freeman	6
Liam Hemsworth	5
Mark Ruffalo	4
Scarlett Johansson	4
Chiwetel Ejiofor	4
Other values (783)	977

Common Values
Length

Value	Count	Frequency (%)
Morgan Freeman	6	0.6%
Liam Hemsworth	5	0.5%
Mark Ruffalo	4	0.4%
Scarlett Johansson	4	0.4%
Chiwetel Ejiofor	4	0.4%
Rupert Grint	4	0.4%
Samuel L. Jackson	4	0.4%
Anna Kendrick	4	0.4%
Willem Dafoe	4	0.4%
Owen Wilson	4	0.4%
Other values (778)	957	95.7%

Length

Max length	26
Median length	14
Mean length	14.15
Min length	7

Actor-4
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count	897
Unique (%)	89.8%
Missing	1
Missing (%)	0.1%
Memory size	7.8 KiB

Woody Harrelson	5
Ralph Fiennes	4
Mark Strong	3
Emily Blunt	3
Ben Kingsley	3
Other values (892)	981

Common Values
Length

Value	Count	Frequency (%)
Woody Harrelson	5	0.5%
Ralph Fiennes	4	0.4%
Mark Strong	3	0.3%
Emily Blunt	3	0.3%
Ben Kingsley	3	0.3%
Judi Dench	3	0.3%
Chloë Grace Moretz	3	0.3%
Michael Caine	3	0.3%
Philip Seymour Hoffman	3	0.3%
Stellan Skarsgård	3	0.3%
Other values (887)	966	96.6%

Length

Max length	27
Median length	13
Mean length	13.885
Min length	3

Genre-1
Categorical

Distinct count	13
Unique (%)	1.3%
Missing	0
Missing (%)	0.0%
Memory size	7.8 KiB

Action	293
Drama	195
Comedy	175
Adventure	75
Crime	71
Other values (8)	191

Common Values
Length

Value	Count	Frequency (%)
Action	293	29.3%
Drama	195	19.5%
Comedy	175	17.5%
Adventure	75	7.5%
Crime	71	7.1%
Biography	64	6.4%
Animation	49	4.9%
Horror	46	4.6%
Mystery	13	1.3%
Thriller	10	1.0%
Other values (3)	9	0.9%

Length

Max length	9
Median length	6
Mean length	6.337
Min length	5

Genre-2
Categorical

MISSING

Distinct count	19
Unique (%)	2.1%
Missing	105
Missing (%)	10.5%
Memory size	7.8 KiB

Drama	238
Adventure	175
Romance	69
Comedy	62
Crime	58
Other values (14)	293

Common Values
Length

Value	Count	Frequency (%)
Drama	238	23.8%
Adventure	175	17.5%
Romance	69	6.9%
Comedy	62	6.2%
Crime	58	5.8%
Thriller	52	5.2%
Mystery	49	4.9%
Horror	49	4.9%
Fantasy	35	3.5%
Sci-Fi	28	2.8%
Other values (9)	80	8.0%
(Missing)	105	10.5%

Length

Max length	9
Median length	6
Mean length	6.202
Min length	3

Genre-3
Categorical

MISSING

Distinct count	18
Unique (%)	2.7%
Missing	340
Missing (%)	34.0%
Memory size	7.8 KiB

Thriller	133
Sci-Fi	89
Drama	80
Romance	70
Fantasy	62
Other values (13)	226

Common Values
Length

Value	Count	Frequency (%)
Thriller	133	13.3%
Sci-Fi	89	8.9%
Drama	80	8.0%
Romance	70	7.0%
Fantasy	62	6.2%
Mystery	44	4.4%
Comedy	42	4.2%
Horror	24	2.4%
Family	24	2.4%
History	21	2.1%
Other values (8)	71	7.1%
(Missing)	340	34.0%

Length

Max length	9
Median length	6
Mean length	5.336
Min length	3

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

First rows

	Rank	Title	Description	Director	Actors	Year	Runtime (Minutes)	Rating	Votes	Revenue (Millions)	Metascore	Actor-1	Actor-2	Actor-3	Actor-4	Genre-1	Genre-2	Genre-3
0	1	Guardians of the Galaxy	A group of intergalactic criminals are forced to work together to stop a fanatical warrior from taking control of the universe.	James Gunn	Chris Pratt, Vin Diesel, Bradley Cooper, Zoe Saldana	2014	121	8.1	757074	333.13	76.0	Chris Pratt	Vin Diesel	Bradley Cooper	Zoe Saldana	Action	Adventure	Sci-Fi
1	2	Prometheus	Following clues to the origin of mankind, a team finds a structure on a distant moon, but they soon realize they are not alone.	Ridley Scott	Noomi Rapace, Logan Marshall-Green, Michael Fassbender, Charlize Theron	2012	124	7.0	485820	126.46	65.0	Noomi Rapace	Logan Marshall-Green	Michael Fassbender	Charlize Theron	Adventure	Mystery	Sci-Fi
2	3	Split	Three girls are kidnapped by a man with a diagnosed 23 distinct personalities. They must try to escape before the apparent emergence of a frightful new 24th.	M. Night Shyamalan	James McAvoy, Anya Taylor-Joy, Haley Lu Richardson, Jessica Sula	2016	117	7.3	157606	138.12	62.0	James McAvoy	Anya Taylor-Joy	Haley Lu Richardson	Jessica Sula	Horror	Thriller	NaN
3	4	Sing	In a city of humanoid animals, a hustling theater impresario's attempt to save his theater with a singing competition becomes grander than he anticipates even as its finalists' find that their lives will never be the same.	Christophe Lourdelet	Matthew McConaughey,Reese Witherspoon, Seth MacFarlane, Scarlett Johansson	2016	108	7.2	60545	270.32	59.0	Matthew McConaughey	Reese Witherspoon	Seth MacFarlane	Scarlett Johansson	Animation	Comedy	Family
4	5	Suicide Squad	A secret government agency recruits some of the most dangerous incarcerated super-villains to form a defensive task force. Their first mission: save the world from the apocalypse.	David Ayer	Will Smith, Jared Leto, Margot Robbie, Viola Davis	2016	123	6.2	393727	325.02	40.0	Will Smith	Jared Leto	Margot Robbie	Viola Davis	Action	Adventure	Fantasy
5	6	The Great Wall	European mercenaries searching for black powder become embroiled in the defense of the Great Wall of China against a horde of monstrous creatures.	Yimou Zhang	Matt Damon, Tian Jing, Willem Dafoe, Andy Lau	2016	103	6.1	56036	45.13	42.0	Matt Damon	Tian Jing	Willem Dafoe	Andy Lau	Action	Adventure	Fantasy
6	7	La La Land	A jazz pianist falls for an aspiring actress in Los Angeles.	Damien Chazelle	Ryan Gosling, Emma Stone, Rosemarie DeWitt, J.K. Simmons	2016	128	8.3	258682	151.06	93.0	Ryan Gosling	Emma Stone	Rosemarie DeWitt	J.K. Simmons	Comedy	Drama	Music
7	8	Mindhorn	A has-been actor best known for playing the title character in the 1980s detective series "Mindhorn" must work with the police when a serial killer says that he will only speak with Detective Mindhorn, whom he believes to be a real person.	Sean Foley	Essie Davis, Andrea Riseborough, Julian Barratt,Kenneth Branagh	2016	89	6.4	2490	NaN	71.0	Essie Davis	Andrea Riseborough	Julian Barratt	Kenneth Branagh	Comedy	NaN	NaN
8	9	The Lost City of Z	A true-life drama, centering on British explorer Col. Percival Fawcett, who disappeared while searching for a mysterious city in the Amazon in the 1920s.	James Gray	Charlie Hunnam, Robert Pattinson, Sienna Miller, Tom Holland	2016	141	7.1	7188	8.01	78.0	Charlie Hunnam	Robert Pattinson	Sienna Miller	Tom Holland	Action	Adventure	Biography
9	10	Passengers	A spacecraft traveling to a distant colony planet and transporting thousands of people has a malfunction in its sleep chambers. As a result, two passengers are awakened 90 years early.	Morten Tyldum	Jennifer Lawrence, Chris Pratt, Michael Sheen,Laurence Fishburne	2016	116	7.0	192177	100.01	41.0	Jennifer Lawrence	Chris Pratt	Michael Sheen	Laurence Fishburne	Adventure	Drama	Romance

Last rows

	Rank	Title	Description	Director	Actors	Year	Runtime (Minutes)	Rating	Votes	Revenue (Millions)	Metascore	Actor-1	Actor-2	Actor-3	Actor-4	Genre-1	Genre-2	Genre-3
990	991	Underworld: Rise of the Lycans	An origins story centered on the centuries-old feud between the race of aristocratic vampires and their onetime slaves, the Lycans.	Patrick Tatopoulos	Rhona Mitra, Michael Sheen, Bill Nighy, Steven Mackintosh	2009	92	6.6	129708	45.80	44.0	Rhona Mitra	Michael Sheen	Bill Nighy	Steven Mackintosh	Action	Adventure	Fantasy
991	992	Taare Zameen Par	An eight-year-old boy is thought to be a lazy trouble-maker, until the new art teacher has the patience and compassion to discover the real problem behind his struggles in school.	Aamir Khan	Darsheel Safary, Aamir Khan, Tanay Chheda, Sachet Engineer	2007	165	8.5	102697	1.20	42.0	Darsheel Safary	Aamir Khan	Tanay Chheda	Sachet Engineer	Drama	Family	Music
992	993	Take Me Home Tonight	Four years after graduation, an awkward high school genius uses his sister's boyfriend's Labor Day party as the perfect opportunity to make his move on his high school crush.	Michael Dowse	Topher Grace, Anna Faris, Dan Fogler, Teresa Palmer	2011	97	6.3	45419	6.92	NaN	Topher Grace	Anna Faris	Dan Fogler	Teresa Palmer	Comedy	Drama	Romance
993	994	Resident Evil: Afterlife	While still out to destroy the evil Umbrella Corporation, Alice joins a group of survivors living in a prison surrounded by the infected who also want to relocate to the mysterious but supposedly unharmed safe haven known only as Arcadia.	Paul W.S. Anderson	Milla Jovovich, Ali Larter, Wentworth Miller,Kim Coates	2010	97	5.9	140900	60.13	37.0	Milla Jovovich	Ali Larter	Wentworth Miller	Kim Coates	Action	Adventure	Horror
994	995	Project X	3 high school seniors throw a birthday party to make a name for themselves. As the night progresses, things spiral out of control as word of the party spreads.	Nima Nourizadeh	Thomas Mann, Oliver Cooper, Jonathan Daniel Brown, Dax Flame	2012	88	6.7	164088	54.72	48.0	Thomas Mann	Oliver Cooper	Jonathan Daniel Brown	Dax Flame	Comedy	NaN	NaN
995	996	Secret in Their Eyes	A tight-knit team of rising investigators, along with their supervisor, is suddenly torn apart when they discover that one of their own teenage daughters has been brutally murdered.	Billy Ray	Chiwetel Ejiofor, Nicole Kidman, Julia Roberts, Dean Norris	2015	111	6.2	27585	NaN	45.0	Chiwetel Ejiofor	Nicole Kidman	Julia Roberts	Dean Norris	Crime	Drama	Mystery
996	997	Hostel: Part II	Three American college students studying abroad are lured to a Slovakian hostel, and discover the grim reality behind it.	Eli Roth	Lauren German, Heather Matarazzo, Bijou Phillips, Roger Bart	2007	94	5.5	73152	17.54	46.0	Lauren German	Heather Matarazzo	Bijou Phillips	Roger Bart	Horror	NaN	NaN
997	998	Step Up 2: The Streets	Romantic sparks occur between two dance students from different backgrounds at the Maryland School of the Arts.	Jon M. Chu	Robert Hoffman, Briana Evigan, Cassie Ventura, Adam G. Sevani	2008	98	6.2	70699	58.01	50.0	Robert Hoffman	Briana Evigan	Cassie Ventura	Adam G. Sevani	Drama	Music	Romance
998	999	Search Party	A pair of friends embark on a mission to reunite their pal with the woman he was going to marry.	Scot Armstrong	Adam Pally, T.J. Miller, Thomas Middleditch,Shannon Woodward	2014	93	5.6	4881	NaN	22.0	Adam Pally	T.J. Miller	Thomas Middleditch	Shannon Woodward	Adventure	Comedy	NaN
999	1000	Nine Lives	A stuffy businessman finds himself trapped inside the body of his family's cat.	Barry Sonnenfeld	Kevin Spacey, Jennifer Garner, Robbie Amell,Cheryl Hines	2016	87	5.3	12435	19.64	11.0	Kevin Spacey	Jennifer Garner	Robbie Amell	Cheryl Hines	Comedy	Family	Fantasy

Overview

Variables

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows